The invention relates to a lateral neural network structure comprising a layer having a plurality of neurons comprising means for optical lateral interconnection.
Neural networks are generally classified in one of three classes, feedforward, recurrent and lateral. In the feedforward type, neuron connections are only in the forward direction, whereas in the recurrent type, they are both forward and backward. In the lateral type, there are lateral connections between neurons of at least one layer. These connections may be inhibitory (negative) and/or excitatory (positive). The invention relates to neural networks of this type.
Use of lateral neural networks is important for some processing applications. One such application is retinal processing. Features of retinal processing are contrast enhancement and local intensity independence. For example, in U.S. Pat. No. 5,033,103, a system is disclosed which enhances edges, eliminates brightness variations and suppresses noise.
Lateral neural networks are also important in achieving unsupervised and self-organising sub-systems. Large scale lateral inhibition can give rise to competitive or "winner-take-all" behaviour within an area defined by the range of the inhibition. When excitatory connections are used also, topographic or computational mapping can be established. This is because if a particular node responds to a given input, nearby nodes may also partly respond. There is extensive evidence from neuroscience as to the importance of topographic mappings and indeed it is regarded as being a building block in the infrastructure of information processing in the nervous system.
At present, most electronic and opto-electronic neural networks have inhibitory connections only. Optics have major advantages for the implementation of such dense, recurrent type interconnections. An example of such a network is disclosed in the paper "Lateral inhibitory action in an optical neural network using an internal-light-coupled optical device array" by Wataru Kawakami, Ken-ichi Kitayama, Yoshinori Nakano and-Masahiro Ikeda in Optics Letters Vol 16, No. 13 Jul. 1, 1991. In this paper, a structure is disclosed whereby each neuron comprises a light-emitting section surrounded by a detecting section for inhibitory interconnections. In the neuron, an array plane and a reflector have holes which must be aligned so that almost all the external light input through the hole which corresponds to an excitatory signal illuminates the light emitting section of the unit. Although it is known to provide both inhibitory and excitatory lateral interconnections in an electrical neural network, as described in European Specification No. 0 349 007 (Hitachi), this is more difficult to achieve optically because light is a positive, definite quantity. The previous approach has been to differentiate the signals by some means such as by wavelength or polarisation, with individual sources and detectors. This enforces very high tolerances on aligning the individual sources with the diffractive elements and detectors and also greatly complicates the individual pixel layout.
The invention is directed towards overcoming these problems.